
Lead Data Analyst
1 week ago
About the Role
We are seeking a highly skilled Data Scientist to join our data and AI team. The successful candidate will be responsible for developing and deploying advanced machine learning models to solve business problems, drive data-based decision-making, and support product development.
Main Responsibilities:
- Design, build, and optimize supervised, unsupervised, and deep learning models for various business problems.
- Clean, transform, and analyze structured and unstructured data; identify significant features.
- Develop end-to-end AI pipelines and integrate models into production systems using APIs or deployment frameworks.
- Work closely with domain experts and engineers to understand requirements and translate them into data science solutions.
- Track model performance (e.g., RMSE, F1 score, ROC AUC), and prepare technical documentation and reports.
- Stay up to date with latest AI/ML techniques (e.g., LLMs, transformers, reinforcement learning) and propose innovative applications.
Requirements
- Bachelors or Masters degree in Computer Science, Statistics, Mathematics, Data Science, or related field.
- 4- 6 years of hands-on experience in: Python, R, SQL Machine Learning frameworks (e.g., Scikit-learn, XGBoost, LightGBM) Deep Learning (e.g., TensorFlow, PyTorch, Keras) Data manipulation and visualization (e.g., Pandas, NumPy, Matplotlib, Seaborn) Model deployment tools (e.g., Flask, FastAPI, Docker, MLflow) Experience with cloud platforms (AWS/GCP/Azure) and MLOps tools Familiarity with large-scale data processing (e.g., Spark, Dask) is a plus Exposure to NLP, computer vision, or generative AI (OpenAI, Hugging Face, LangChain) is highly desirable.
- Strong analytical and communication skills.
- Nice to Have: Experience in industry-specific AI applications (e.g., fintech, healthcare, retail) Contribution to open-source projects or ML competitions (e.g., Kaggle) Certifications in Data Science / AI from recognized platforms.
What We Offer
- A dynamic and collaborative work environment
- Opportunities to work on cutting-edge AI/ML projects
- Flexible work arrangements
- Competitive compensation and performance bonuses
- Continuous learning support through training and certifications
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